Senior AI-First Data Engineer

About Smartcat

Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises.

We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one.

Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale.

Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us.

Join us in unlocking global potential, one human and agent team at a time.

WHY YOU SHOULD JOIN OUR TEAM

You'll help build the intelligence layer that powers decision-making, AI agents, automation, and business operations across Smartcat — on a greenfield cloud data platform, transitioning from legacy on-premise, batch architectures to cloud-native, streaming-first infrastructure. This is a chance to shape how Smartcat scales its data capabilities over the next several years, directly aligned with the company's transformation into an AI-native, agentic platform.

MISSION

Help transform Smartcat's data platform into an AI-native foundation where business data becomes discoverable, actionable, and consumable by both humans and AI agents — partnering across Data, Product, Engineering, GTM, and AI teams to enable self-service analytics, intelligent automation, and agent-driven decision support.

OUTCOMES

Evolve Smartcat's data architecture into a scalable, cloud-native, AI-first platform, leading the transition from batch-oriented pipelines to near real-time and streaming systems

Improve reliability, observability, governance, and performance across the data stack, establishing engineering standards and best practices

Turn business data into AI-ready assets — building data products consumable by AI agents, analytics systems, and business users, with semantic layers and metadata management

Use AI to accelerate development, testing, documentation, monitoring, and operational workflows, and design systems that let AI agents query, understand, and act on business data safely

Improve business intelligence and data accessibility — making analytics simpler for non-technical stakeholders and enabling self-service without sacrificing governance or quality

Raise the engineering bar through mentorship, code reviews, architecture leadership, and knowledge sharing across Data and Analytics Engineering

HOW YOU'LL RAMP

By Day 30:

Get deep on Smartcat's current data architecture, the greenfield cloud platform build, and the transition plan from batch to streaming

Meet your partners across Data, Product, Engineering, GTM, and AI teams to understand current pain points and priorities

Get hands-on with the core stack (Databricks, dbt, Airflow, Python, SQL) and current BI tooling (e.g., Omni)

By Day 60:

Contribute to at least one concrete piece of the Next Generation Data Platform build (pipeline, streaming component, or data product)

Have identified and started applying at least one AI-powered workflow to accelerate your own engineering work (testing, documentation, debugging)

Begin shaping a semantic layer, metadata structure, or data product aimed at AI-agent or business-user consumption

By Day 90:

Own a defined piece of architectur